Antarctica - ASV analysis
Antarctica - ASV analysis
- Initialize
- Get the list of samples for GenBank submission - 2020-07-09 - DO NOT RUN
- Get the Antarctica ASVs
- Get the different fraction separately
- Surface samples
- NMDS
- Vertical profile
- Compare the contributions of CLASS and SPECIES using the different methods
- Sample by sample comparison
- Define upset function
- Global comparison of species found with the 3 methods
- Write to Excel file
- Comparison of species found in the different fractions for 18S filter and 18S sorted
- Comparison of species found in the different fractions for 18S filter
- Comparison of species found in the different fractions for 18S sort
- Figures
- Saving Tables to Latex
Initialize
Libraries
if(any(grepl("package:dvutils", search()))) detach("package:dvutils", unload=TRUE)
library(dvutils)
library(stringr)
library(ggplot2)
library(dplyr)
library(tidyr)
library(tibble)
library(readr)
library(maps)
library(glue)
library(readxl)
library(rlang)
library(phyloseq)
library(knitr)
library(rmdformats)
library(patchwork)
# library(pr2database)
# data("pr2")Markdown
Get the list of samples for GenBank submission - 2020-07-09 - DO NOT RUN
Get the Antarctica ASVs
| set id | description |
|---|---|
| 16 | Antar_2015_18S_V4 |
| 17 | Antar_2015_16S_plastid |
| 18 | Antar_2015_18S_V4_sorted |
- Only use asv for which supergroup_boot >= 90
- Only keep photosynthetic groups abd exclude dinoflagellates
Initialize constants
Read the data from the database (only done once) - DO NOT RUN !
temp <- list()
# Export as specific data set as a phyloseq file
for (i in 1:3) {
temp <- metapr2_export_asv(dataset_id_selected = i + 15, taxo_level = division, taxo_name = taxon_selected, export_phyloseq = TRUE, export_long_xls = FALSE,
export_wide_xls = TRUE, export_fasta = TRUE, export_sample_xls = TRUE, boot_min = 90, boot_level = supergroup_boot, directory = "../dada2/")
}
rm(temp)Read the Phyloseq files from the disk
- Only keep station 6
- Do not consider TFF samples
for (i in 1:3) {
ps[[sample_type[i]]] <- readRDS(str_c("../dada2/phyloseq_metapr2_asv_set_", i + 15, "_photo.rda"))
# Filter out station 14
ps[[sample_type[i]]] <- subset_samples(ps[[sample_type[i]]], station_id == "6")
# Filter out TFF concentrated samples
if (i == 3) {
ps[[sample_type[i]]] <- subset_samples(ps[[sample_type[i]]], is.na(sample_concentration))
}
ps[[sample_type[i]]] <- ps[[sample_type[i]]] %>% # Filter ASVs that are absent
filter_taxa(function(x) sum(x) > 0, TRUE) %>% # Filter Paraphysomonas
subset_taxa(family != "Chrysophyceae_Clade-F")
# Label samples with date
sample_data(ps[[sample_type[i]]])$sample_label <- as.character(sample_data(ps[[sample_type[i]]])$date)
# Add TFF to sample name sample_data(ps[[one_sample_type]])$sample_label <- str_c(sample_data(ps[[one_sample_type]])$metadata_code,
# str_replace_na(sample_data(ps[[one_sample_type]])$sample_concentration, ''), sep = '.' )
print(glue("Phyloseq - {sample_type[i]}"))
print(ps[[sample_type[i]]])
print(glue("Mean number of reads: {mean(sample_sums(ps[[ sample_type[i] ]]))}"))
cat("============================\n")
mean(sample_sums(ps[[sample_type[i]]]))
}Phyloseq - 18S filter
phyloseq-class experiment-level object
otu_table() OTU Table: [ 681 taxa and 120 samples ]
sample_data() Sample Data: [ 120 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 681 taxa by 8 taxonomic ranks ]
Mean number of reads: 27029.1083333333
============================
Phyloseq - 16S plastid
phyloseq-class experiment-level object
otu_table() OTU Table: [ 417 taxa and 100 samples ]
sample_data() Sample Data: [ 100 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 417 taxa by 8 taxonomic ranks ]
Mean number of reads: 35058.32
============================
Phyloseq - 18S sort
phyloseq-class experiment-level object
otu_table() OTU Table: [ 195 taxa and 40 samples ]
sample_data() Sample Data: [ 40 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 195 taxa by 8 taxonomic ranks ]
Mean number of reads: 31960.325
============================
[1] "sample_id" "file_name" "NCBI_run" "sample_name"
[5] "sample_code" "metadata_code" "DNA_RNA" "fraction_name"
[9] "fraction_name_original" "fraction_min" "fraction_max" "reads_total"
[13] "metadata_id" "project" "station_id" "station_id_num"
[17] "year" "date" "time" "season"
[21] "depth_level" "depth" "substrate" "latitude"
[25] "longitude" "site_name" "country" "oceanic_region"
[29] "temperature" "salinity" "pH" "O2"
[33] "fluorescence" "Chla" "Chla_0.2_3.um" "NO2"
[37] "NO3" "PO4" "Si" "bact_ml"
[41] "peuk_ml" "neuk_ml" "crypto_ml" "dataset_code"
[45] "dataset_name" "processing_pipeline_metapr2" "processing_date" "sequencing_technology"
[49] "sequencing_type" "sequencing_company" "region" "ecosystem"
[53] "lat_min" "lat_max" "long_min" "long_max"
[57] "data_available" "bioproject_accession" "bioproject_link" "sample_label"
[1] 27029.11
Get the different fraction separately
fraction_filter <- c(0.2, 3, 20)
fraction_sort <- c("pico", "nano")
sample_type_filtered <- c(str_c(sample_type[1], fraction_filter, "um", sep = " "), str_c(sample_type[2], fraction_filter, "um", sep = " "), str_c(sample_type[3],
fraction_sort, sep = " "))
# Export as specific data set as a phyloseq file
for (one_sample_type in sample_type[1:2]) {
for (one_fraction in fraction_filter) {
one_sample_type_filtered <- c(str_c(one_sample_type, one_fraction, "um", sep = " "))
ps[[one_sample_type_filtered]] <- ps[[one_sample_type]] %>% subset_samples(fraction_min == one_fraction) %>% filter_taxa(function(x) sum(x) >
0, TRUE)
print(glue("Phyloseq - {one_sample_type_filtered}"))
print(ps[[one_sample_type_filtered]])
cat("============================\n")
}
}Phyloseq - 18S filter 0.2 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 317 taxa and 42 samples ]
sample_data() Sample Data: [ 42 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 317 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 3 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 366 taxa and 43 samples ]
sample_data() Sample Data: [ 43 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 366 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 20 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 299 taxa and 35 samples ]
sample_data() Sample Data: [ 35 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 299 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 0.2 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 181 taxa and 28 samples ]
sample_data() Sample Data: [ 28 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 181 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 3 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 219 taxa and 41 samples ]
sample_data() Sample Data: [ 41 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 219 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 20 um
phyloseq-class experiment-level object
otu_table() OTU Table: [ 212 taxa and 31 samples ]
sample_data() Sample Data: [ 31 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 212 taxa by 8 taxonomic ranks ]
============================
# Sorted samples
for (one_sample_type in sample_type[3]) {
for (one_fraction in fraction_sort) {
one_sample_type_filtered <- c(str_c(one_sample_type, one_fraction, sep = " "))
ps[[one_sample_type_filtered]] <- ps[[one_sample_type]] %>% subset_samples(fraction_name == one_fraction) %>% filter_taxa(function(x) sum(x) >
0, TRUE)
print(glue("Phyloseq - {one_sample_type_filtered}"))
print(ps[[one_sample_type_filtered]])
cat("============================\n")
}
}Phyloseq - 18S sort pico
phyloseq-class experiment-level object
otu_table() OTU Table: [ 123 taxa and 20 samples ]
sample_data() Sample Data: [ 20 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 123 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort nano
phyloseq-class experiment-level object
otu_table() OTU Table: [ 107 taxa and 20 samples ]
sample_data() Sample Data: [ 20 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 107 taxa by 8 taxonomic ranks ]
============================
Surface samples
- Only surface considered (5 m)
- Very important, must remove taxa that are not present in the filtered samples
sample_type_surface <- str_c(sample_type_all, " surface")
for (one_sample_type in sample_type_all) {
one_sample_type_surface = str_c(one_sample_type, " surface")
ps[[one_sample_type_surface]] <- ps[[one_sample_type]] %>% subset_samples(depth_level == "surface") %>% filter_taxa(function(x) sum(x) > 0,
TRUE)
# Rename the samples
if (!str_detect(one_sample_type_surface, "sort")) {
sample_names(ps[[one_sample_type_surface]]) <- str_c(as.character(sample_data(ps[[one_sample_type_surface]])$date), as.character(sample_data(ps[[one_sample_type_surface]])$depth),
"m", as.character(sample_data(ps[[one_sample_type_surface]])$fraction_min), sep = "_")
} else {
sample_names(ps[[one_sample_type_surface]]) <- str_c(as.character(sample_data(ps[[one_sample_type_surface]])$date), as.character(sample_data(ps[[one_sample_type_surface]])$depth),
"m", as.character(sample_data(ps[[one_sample_type_surface]])$fraction_name), sep = "_")
}
print(glue("Phyloseq - {one_sample_type_surface}"))
print(ps[[one_sample_type_surface]])
cat("============================\n")
}Phyloseq - 18S filter surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 383 taxa and 50 samples ]
sample_data() Sample Data: [ 50 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 383 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 236 taxa and 40 samples ]
sample_data() Sample Data: [ 40 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 236 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 114 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 114 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 0.2 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 187 taxa and 17 samples ]
sample_data() Sample Data: [ 17 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 187 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 3 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 225 taxa and 18 samples ]
sample_data() Sample Data: [ 18 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 225 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S filter 20 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 199 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 199 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 0.2 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 112 taxa and 11 samples ]
sample_data() Sample Data: [ 11 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 112 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 3 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 142 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 142 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 16S plastid 20 um surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 120 taxa and 13 samples ]
sample_data() Sample Data: [ 13 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 120 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort pico surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 65 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 65 taxa by 8 taxonomic ranks ]
============================
Phyloseq - 18S sort nano surface
phyloseq-class experiment-level object
otu_table() OTU Table: [ 70 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 70 taxa by 8 taxonomic ranks ]
============================
Normalize and transform to long form
for (one_sample_type in sample_type_surface) {
cat(one_sample_type)
cat("\n============================")
ps[[one_sample_type]] <- phyloseq_normalize_median(ps[[one_sample_type]])
long[[one_sample_type]] <- phyloseq_transform_to_long(ps[[one_sample_type]])
cat("\n")
}18S filter surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 383 taxa and 50 samples ]
sample_data() Sample Data: [ 50 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 383 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 23194
16S plastid surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 236 taxa and 40 samples ]
sample_data() Sample Data: [ 40 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 236 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 28885
18S sort surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 114 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 114 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 27275
18S filter 0.2 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 187 taxa and 17 samples ]
sample_data() Sample Data: [ 17 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 187 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 14645
18S filter 3 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 225 taxa and 18 samples ]
sample_data() Sample Data: [ 18 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 225 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 24783
18S filter 20 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 199 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 199 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 29427
16S plastid 0.2 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 112 taxa and 11 samples ]
sample_data() Sample Data: [ 11 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 112 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 28471
16S plastid 3 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 142 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 142 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 31801
16S plastid 20 um surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 120 taxa and 13 samples ]
sample_data() Sample Data: [ 13 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 120 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 25641
18S sort pico surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 65 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 65 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 33258
18S sort nano surface
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 70 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 70 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 21650
List of classes
classes <- data.frame(division = NULL, class = NULL)
for (one_sample_type in sample_type_surface[1:3]) {
classes <- bind_rows(classes, select(long[[one_sample_type]], division, class))
}
classes <- classes %>% distinct(division, class) %>% arrange(division, class)
# print(classes, n=50)
knitr::kable(classes)| division | class |
|---|---|
| Chlorophyta | Chlorophyceae |
| Chlorophyta | Mamiellophyceae |
| Chlorophyta | Palmophyllophyceae |
| Chlorophyta | Prasino-Clade-V |
| Chlorophyta | Pyramimonadophyceae |
| Chlorophyta | Trebouxiophyceae |
| Chlorophyta | Ulvophyceae |
| Cryptophyta | Cryptophyceae |
| Haptophyta | Prymnesiophyceae |
| Ochrophyta | Bacillariophyta |
| Ochrophyta | Bolidophyceae |
| Ochrophyta | Chrysophyceae |
| Ochrophyta | Dictyochophyceae |
| Ochrophyta | MOCH-1 |
| Ochrophyta | MOCH-2 |
| Ochrophyta | Pelagophyceae |
| Ochrophyta | Phaeophyceae |
| Ochrophyta | Xanthophyceae |
| Rhodophyta | Bangiophyceae |
| Rhodophyta | Florideophyceae |
Treemaps
treemap_class <- list()
treemap_genus <- list()
for (one_sample_type in sample_type_surface) {
treemap_class[[one_sample_type]] <- phyloseq_long_treemap(long[[one_sample_type]], division, class, str_c(one_sample_type, " - Class"), colors = class_colors)
treemap_genus[[one_sample_type]] <- phyloseq_long_treemap(long[[one_sample_type]], class, genus, str_c(one_sample_type, " - Genus"), colors = genus_colors)
}ASVs bargraphs
bargraph_asv <- list()
bargraph_species <- list()
for (one_sample_type in sample_type_surface) {
bargraph_asv[[one_sample_type]] <- phyloseq_long_bargraph(long[[one_sample_type]], text_scaling = 0.75, n_bars = 20, use_asv = TRUE, title = one_sample_type,
taxo_level_fill = class, taxo_colors_fill = class_colors)
bargraph_species[[one_sample_type]] <- phyloseq_long_bargraph(long[[one_sample_type]], text_scaling = 0.75, n_bars = 20, use_asv = FALSE, title = one_sample_type,
taxo_level_fill = class, taxo_colors_fill = class_colors)
} ## Barplots per sample
bargraph_sample <- list()
for (one_sample_type in sample_type_surface[4:11]) {
bargraph_sample[[one_sample_type]] <- plot_bar(ps[[one_sample_type]], x = "sample_label", fill = "class") + geom_bar(aes(color = class, fill = class),
stat = "identity", position = "stack") + ggtitle(str_c("Class level - ", one_sample_type)) + theme(axis.text.y = element_text(size = 10)) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5)) + coord_flip() + scale_fill_viridis_d() + scale_color_viridis_d()
print(bargraph_sample[[one_sample_type]])
}Heatmaps
Filter : Dictyo / Chrysophyceae /Pelago /Bacili / Crypto / Pyrami / Mamiello
Class
Most abundant 10%
heatmap_class_abundant <- list()
for (one_sample_type in sample_type_surface[4:11]) {
ps_heat <- tax_glom(ps[[one_sample_type]], taxrank = "class") %>% phyloseq_filter_abundant_taxa(fraction_min = 0.1)
heatmap_class_abundant[[one_sample_type]] <- plot_heatmap(ps_heat, method = "NMDS", distance = "bray", taxa.label = "class", taxa.order = "division",
sample.label = "sample_label", sample.order = "sample_label", low = "beige", high = "red", na.value = "beige", trans = NULL, title = one_sample_type) +
xlab("") + ylab("")
# plot(heatmap(otu_table(ps_heat)))
print(heatmap_class_abundant[[one_sample_type]])
}
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 7 taxa and 17 samples ]
sample_data() Sample Data: [ 17 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 7 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 13806
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 7 taxa and 18 samples ]
sample_data() Sample Data: [ 18 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 7 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 23366
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 5 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 5 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 27860
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 4 taxa and 11 samples ]
sample_data() Sample Data: [ 11 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 4 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 27592
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 5 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 5 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 31460
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 4 taxa and 13 samples ]
sample_data() Sample Data: [ 13 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 4 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 24881
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 4 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 4 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 32016
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 4 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 4 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 21054
Selected
class_selected <- c("Dictyochophyceae", "Chrysophyceae", "Pelagophyceae", "Bacillariophyta", "Prymnesiophyceae", "Cryptophyceae", "Pyramimonadophyceae",
"Mamiellophyceae")
heatmap_class_selected <- list()
for (one_sample_type in sample_type_surface[4:11]) {
# for (one_sample_type in sample_type_surface[4:4]) {
reads_max <- case_when(str_detect(one_sample_type, "18S filter") ~ 10000, str_detect(one_sample_type, "16S plastid") ~ 30000, str_detect(one_sample_type,
"18S sort") ~ 10000)
if (str_detect(one_sample_type, "18S sort")) {
class_selected <- c("Pelagophyceae", "Bacillariophyta", "Prymnesiophyceae", "Cryptophyceae", "Mamiellophyceae")
}
ps_heat <- tax_glom(ps[[one_sample_type]], taxrank = "class") %>% subset_taxa(class %in% class_selected)
# Try to order by division and class... tax_table <- data.frame(tax_table(ps_heat)@.Data) taxa_names(ps_heat) <- str_c(tax_table$division,
# tax_table$class, sep=' - ')
gg <- plot_heatmap(ps_heat, method = "NMDS", distance = "bray", taxa.label = "class", taxa.order = "class", sample.label = "sample_label", sample.order = "sample_label",
low = "beige", high = "red", na.value = "gray95", trans = NULL, title = one_sample_type) + theme(axis.text.x = element_text(angle = 45,
hjust = 1, vjust = 1), axis.title.x = element_blank(), axis.title.y = element_blank(), panel.background = element_rect(fill = "grey50"),
panel.grid.major = element_blank()) + scale_fill_gradient(limits = c(0, reads_max), low = "beige", high = "red", na.value = "red")
if (str_detect(one_sample_type, "18S filter 0.2"))
gg <- gg + expand_limits(y = c(0.5, 9)) + geom_vline(xintercept = c(3.5, 9.5, 12.5)) + annotate(geom = "text", label = c("summer", "fall",
"spring", "summer"), x = c(2, 6.5, 11, 15), y = 8.65, color = "white", fill = "grey50", hjust = 0.5, vjust = 0, size = 4.5, label.r = unit(0.2,
"lines"))
if (one_sample_type == "18S filter 3 um surface")
gg <- gg + expand_limits(y = c(0.5, 9)) + geom_vline(xintercept = c(4.5, 10.5, 13.5)) + annotate(geom = "text", label = c("summer", "fall",
"spring", "summer"), x = c(2.5, 7.5, 12, 16), y = 8.65, color = "white", fill = "grey50", hjust = 0.5, vjust = 0, size = 4.5, label.r = unit(0.2,
"lines"))
if (one_sample_type == "18S filter 20 um surface")
gg <- gg + expand_limits(y = c(0.5, 9)) + geom_vline(xintercept = c(4.5, 9.5)) + annotate(geom = "text", label = c("summer", "fall", "summer"),
x = c(2.5, 7, 12.5), y = 8.65, color = "white", fill = "grey50", hjust = 0.5, vjust = 0, size = 4.5, label.r = unit(0.2, "lines"))
# plot(heatmap(otu_table(ps_heat))) , trans = scales::log_trans(10)
print(gg)
heatmap_class_selected[[one_sample_type]] <- gg
}Species
Most abundant
heatmap_genus_abundant <- list()
for (one_sample_type in sample_type_surface[4:11]) {
ps_heat <- tax_glom(ps[[one_sample_type]], taxrank = "species") %>% phyloseq_filter_abundant_taxa(fraction_min = 0.1)
heatmap_genus_abundant[[one_sample_type]] <- plot_heatmap(ps_heat, method = "NMDS", distance = "bray", taxa.label = "species", taxa.order = "division",
sample.label = "sample_label", sample.order = "sample_label", low = "beige", high = "red", na.value = "beige", title = one_sample_type)
print(heatmap_genus_abundant[[one_sample_type]])
}
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 10 taxa and 17 samples ]
sample_data() Sample Data: [ 17 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 10 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 11702
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 8 taxa and 18 samples ]
sample_data() Sample Data: [ 18 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 8 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 20199
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 11 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 11 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 26302
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 6 taxa and 11 samples ]
sample_data() Sample Data: [ 11 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 6 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 27286
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 9 taxa and 16 samples ]
sample_data() Sample Data: [ 16 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 9 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 30697
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 8 taxa and 13 samples ]
sample_data() Sample Data: [ 13 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 8 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 24093
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 5 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 5 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 28373
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 6 taxa and 8 samples ]
sample_data() Sample Data: [ 8 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 6 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 19513
Selected
species_selected <- c("Thalassiosira_minima", "Fragilariopsis_cylindrus", "Minidiscus_sp.", "Chaetoceros_neogracilis", "Porosira_glacialis", "Coretrhon_inerme",
"Palmaria_palmata", "Pseudo-nitzchia_seriata", "Micromonas_polaris", "Micromonas_clade_B3", "Bathycoccus_prasinos", "Pyramimonas_gelidicola",
"Geminigera_cryophila", "Pelagophyceae_XXX_sp.", "Phaeocystis_antarctica")
heatmap_species_selected <- list()
for (one_sample_type in sample_type_surface[4:11]) {
# for (one_sample_type in sample_type_surface[4:4]) {
reads_max <- case_when(str_detect(one_sample_type, "18S filter") ~ 10000, str_detect(one_sample_type, "16S plastid") ~ 5000, str_detect(one_sample_type,
"18S sort") ~ 10000)
if (str_detect(one_sample_type, "18S sort")) {
species_selected <- c("Thalassiosira_minima", "Fragilariopsis_cylindrus", "Minidiscus_sp.", "Chaetoceros_neogracilis", "Porosira_glacialis",
"Coretrhon_inerme", "Palmaria_palmata", "Pseudo-nitzchia_seriata", "Micromonas_polaris", "Geminigera_cryophila", "Pelagophyceae_XXX_sp.",
"Phaeocystis_antarctica")
}
ps_heat <- tax_glom(ps[[one_sample_type]], taxrank = "species") %>% subset_taxa(species %in% species_selected)
# Try to order by division and species... tax_table <- data.frame(tax_table(ps_heat)@.Data) taxa_names(ps_heat) <- str_c(tax_table$division,
# tax_table$species, sep=' - ')
gg <- plot_heatmap(ps_heat, method = "NMDS", distance = "bray", taxa.label = "species", taxa.order = "class", sample.label = "sample_label",
sample.order = "sample_label", low = "beige", high = "red", na.value = "gray95", trans = NULL, title = one_sample_type) + theme(axis.text.x = element_text(angle = 45,
hjust = 1, vjust = 1), axis.title.x = element_blank(), axis.title.y = element_blank(), panel.background = element_rect(fill = "grey50"),
panel.grid.major = element_blank()) + scale_fill_gradient(limits = c(0, reads_max), low = "beige", high = "red", na.value = "red")
if (str_detect(one_sample_type, "18S filter 0.2"))
gg <- gg + geom_vline(xintercept = c(3.5, 9.5, 12.5))
if (one_sample_type == "18S filter 3 um surface")
gg <- gg + geom_vline(xintercept = c(4.5, 10.5, 13.5))
if (one_sample_type == "18S filter 20 um surface")
gg <- gg + geom_vline(xintercept = c(4.5, 9.5))
# plot(heatmap(otu_table(ps_heat))) , trans = scales::log_trans(10)
print(gg)
heatmap_species_selected[[one_sample_type]] <- gg
}NMDS
Apply to all samples
nmds_sample <- list()
for (one_sample_type in sample_type_surface[1:3]) {
one_ps <- ps[[one_sample_type]] %>% tax_glom(taxrank = "species")
nmds_sample[[one_sample_type]] <- phyloseq_nmds(one_ps, title = one_sample_type, sample_color = season, sample_shape = fraction_name_original,
taxo_level = class, taxo_colors = class_colors)
}Square root transformation
Wisconsin double standardization
Run 0 stress 0.1714216
Run 1 stress 0.1758561
Run 2 stress 0.1717706
... Procrustes: rmse 0.007217713 max resid 0.02514368
Run 3 stress 0.1759724
Run 4 stress 0.1714241
... Procrustes: rmse 0.0003112062 max resid 0.001279752
... Similar to previous best
Run 5 stress 0.1713535
... New best solution
... Procrustes: rmse 0.003791301 max resid 0.01300957
Run 6 stress 0.1713543
... Procrustes: rmse 0.0002738691 max resid 0.00105073
... Similar to previous best
Run 7 stress 0.1714036
... Procrustes: rmse 0.003856787 max resid 0.01498517
Run 8 stress 0.1758565
Run 9 stress 0.1760002
Run 10 stress 0.1713761
... Procrustes: rmse 0.002503714 max resid 0.01167642
Run 11 stress 0.190753
Run 12 stress 0.1758566
Run 13 stress 0.1778862
Run 14 stress 0.1776749
Run 15 stress 0.1937439
Run 16 stress 0.1713777
... Procrustes: rmse 0.002296881 max resid 0.01177999
Run 17 stress 0.1759718
Run 18 stress 0.1713972
... Procrustes: rmse 0.002984647 max resid 0.0119656
Run 19 stress 0.1866215
Run 20 stress 0.1904543
*** Solution reached
[1] 3
Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(veganifyOTU(physeq)))
Distance: bray
Dimensions: 2
Stress: 0.1713535
Stress type 1, weak ties
Two convergent solutions found after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))'
Square root transformation
Wisconsin double standardization
Run 0 stress 0.1477193
Run 1 stress 0.151694
Run 2 stress 0.1515777
Run 3 stress 0.1720669
Run 4 stress 0.1476132
... New best solution
... Procrustes: rmse 0.008944154 max resid 0.03744427
Run 5 stress 0.1743639
Run 6 stress 0.1651081
Run 7 stress 0.1531319
Run 8 stress 0.1490493
Run 9 stress 0.165109
Run 10 stress 0.1651081
Run 11 stress 0.1925171
Run 12 stress 0.162316
Run 13 stress 0.1737626
Run 14 stress 0.1720647
Run 15 stress 0.1519371
Run 16 stress 0.1736789
Run 17 stress 0.1720671
Run 18 stress 0.1874055
Run 19 stress 0.150668
Run 20 stress 0.1742395
*** No convergence -- monoMDS stopping criteria:
20: stress ratio > sratmax
[1] 3
Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(veganifyOTU(physeq)))
Distance: bray
Dimensions: 2
Stress: 0.1476132
Stress type 1, weak ties
No convergent solutions - best solution after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))'
Square root transformation
Wisconsin double standardization
Run 0 stress 0.05090316
Run 1 stress 0.0524764
Run 2 stress 0.05145132
Run 3 stress 0.05736205
Run 4 stress 0.05466462
Run 5 stress 0.05537261
Run 6 stress 0.06026908
Run 7 stress 0.0524764
Run 8 stress 0.05161248
Run 9 stress 0.05185409
Run 10 stress 0.05723175
Run 11 stress 0.05145131
Run 12 stress 0.05945005
Run 13 stress 0.05440615
Run 14 stress 0.05202902
Run 15 stress 0.3065991
Run 16 stress 0.06090273
Run 17 stress 0.05950989
Run 18 stress 0.05188958
Run 19 stress 0.05220003
Run 20 stress 0.05185435
*** No convergence -- monoMDS stopping criteria:
20: stress ratio > sratmax
[1] 3
Call:
metaMDS(comm = veganifyOTU(physeq), distance = distance)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(veganifyOTU(physeq)))
Distance: bray
Dimensions: 2
Stress: 0.05090316
Stress type 1, weak ties
No convergent solutions - best solution after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(veganifyOTU(physeq)))'
Vertical profile
- Station 6 - 2015-01-16
- Very important, must remove taxa that are not present in the filtered samples
Filter the data
sample_type_profile <- str_c(sample_type_all, " profile")
for (one_sample_type in sample_type_all) {
one_sample_type_profile = str_c(one_sample_type, " profile")
ps[[one_sample_type_profile]] <- ps[[one_sample_type]] %>% subset_samples(station_id == "6") %>% subset_samples(date == "2015-01-16") %>% filter_taxa(function(x) sum(x) >
0, TRUE) %>% phyloseq_normalize_median()
# Rename the samples
if (!str_detect(one_sample_type_profile, "sort")) {
sample_names(ps[[one_sample_type_profile]]) <- str_c(as.character(sample_data(ps[[one_sample_type_profile]])$depth), "m", as.character(sample_data(ps[[one_sample_type_profile]])$fraction_min),
sep = "_")
} else {
sample_names(ps[[one_sample_type_profile]]) <- str_c(as.character(sample_data(ps[[one_sample_type_profile]])$depth), "m", as.character(sample_data(ps[[one_sample_type_profile]])$fraction_name),
sep = "_")
}
print(glue("Phyloseq - {one_sample_type_profile}"))
print(ps[[one_sample_type_profile]])
cat("============================\n")
}
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 172 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 172 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 43461Phyloseq - 18S filter profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 172 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 172 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 107 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 107 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 41130Phyloseq - 16S plastid profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 107 taxa and 15 samples ]
sample_data() Sample Data: [ 15 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 107 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 94 taxa and 10 samples ]
sample_data() Sample Data: [ 10 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 94 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 29304Phyloseq - 18S sort profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 94 taxa and 10 samples ]
sample_data() Sample Data: [ 10 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 94 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 90 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 90 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 30257Phyloseq - 18S filter 0.2 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 90 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 90 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 84 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 84 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 31205Phyloseq - 18S filter 3 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 84 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 84 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 121 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 121 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 58797Phyloseq - 18S filter 20 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 121 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 121 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 46 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 46 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 40267Phyloseq - 16S plastid 0.2 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 46 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 46 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 62 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 62 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 46172Phyloseq - 16S plastid 3 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 62 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 62 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 74 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 74 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 47020Phyloseq - 16S plastid 20 um profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 74 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 60 sample variables ]
tax_table() Taxonomy Table: [ 74 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 63 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 63 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 29412Phyloseq - 18S sort pico profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 63 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 63 taxa by 8 taxonomic ranks ]
============================
==========
phyloseq-class experiment-level object
otu_table() OTU Table: [ 46 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 46 taxa by 8 taxonomic ranks ]
==========
The median number of reads used for normalization is 28502Phyloseq - 18S sort nano profile
phyloseq-class experiment-level object
otu_table() OTU Table: [ 46 taxa and 5 samples ]
sample_data() Sample Data: [ 5 samples by 61 sample variables ]
tax_table() Taxonomy Table: [ 46 taxa by 8 taxonomic ranks ]
============================
Barplots per depth
bargraph_sample <- list()
for (one_sample_type in sample_type_profile[4:11]) {
bargraph_sample[[one_sample_type]] <- plot_bar(ps[[one_sample_type]], x = "depth", fill = "class") + geom_bar(aes(color = class, fill = class),
stat = "identity", position = "stack") + ggtitle(str_c("Class level - ", one_sample_type)) + theme(axis.text.y = element_text(size = 10)) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5)) + coord_flip() + # scale_fill_viridis_d() + scale_color_viridis_d() +
scale_fill_manual(values = class_colors) + scale_color_manual(values = class_colors) + scale_x_reverse() + xlab("Depth (m)") + ylab("Reads") +
theme_bw()
print(bargraph_sample[[one_sample_type]])
}Compare the contributions of CLASS and SPECIES using the different methods
Sample by sample comparison
- Each dot corresponds to the relative contribution of the taxonomic level considered for a sample for which both 18S and 16S has been performed
long_species_sample <- list()
long_class_sample <- list()
for (one_sample_type in sample_type) {
ps_one <- phyloseq_normalize_percent(ps[[one_sample_type]])
long_one <- phyloseq_transform_to_long(ps_one) %>% filter(!is.na(fraction_name_original)) %>% group_by(date, station_id, depth, fraction_name_original,
division, class, order, family, genus, species) %>% summarize(n_reads = sum(n_reads)) %>% ungroup()
long_species_sample[[one_sample_type]] <- long_one
long_one <- phyloseq_transform_to_long(ps_one) %>% filter(!is.na(fraction_name_original)) %>% group_by(date, station_id, depth, fraction_name_original,
division, class) %>% summarize(n_reads = sum(n_reads)) %>% ungroup()
long_class_sample[[one_sample_type]] <- long_one
}
long_compare_species_18S_16S <- full_join(rename(long_species_sample[["18S filter"]], n_reads_18S_filter = n_reads), rename(long_species_sample[["16S plastid"]],
n_reads_16S_plastid = n_reads))
ggplot(long_compare_species_18S_16S, aes(x = n_reads_18S_filter, y = n_reads_16S_plastid)) + geom_point(aes(color = class)) + scale_color_manual(values = class_colors) +
ggtitle("Species")long_compare_class_18S_16S <- long_compare_species_18S_16S %>% group_by(date, station_id, depth, fraction_name_original, division, class) %>% summarize(n_reads_18S_filter = sum(n_reads_18S_filter,
na.rm = TRUE), n_reads_16S_plastid = sum(n_reads_16S_plastid, na.rm = TRUE))
ggplot(long_compare_class_18S_16S, aes(x = n_reads_18S_filter, y = n_reads_16S_plastid)) + geom_point(aes(color = class)) + scale_color_manual(values = class_colors) +
ggtitle("Classes")Define upset function
- Needs only to have 0 and 1 in the matrix
plot_upset_long <- function(long_comparison, file_name) {
long_upset <- long_comparison %>% mutate_if(is.numeric, funs(case_when(is.na(.) ~ 0, TRUE ~ 1))) %>% as.data.frame()
fig_upset <- UpSetR::upset(long_upset, empty.intersections = "on", number.angles = 30, point.size = 12, line.size = 4, mainbar.y.label = "Taxa number",
sets.x.label = "Taxa #", order.by = "freq", text.scale = c(5), mb.ratio = c(0.7, 0.3))
# text.scale = c(intersection size title, intersection size tick labels, set size title, set size tick labels, set names, numbers above bars)
print(fig_upset)
png(file_name, width = 2000, height = 1200, units = "px")
print(fig_upset)
dev.off()
return(fig_upset)
}Global comparison of species found with the 3 methods
Compute table of number of samples for each species (rows) vs the three methods (columns)
Only keep
- 2015 samples because it is the only dataset for which we have the three types of samples
- 0.2 and 3 um fractions (to be comparable with sorting)
Remove species that contains _X
long_species <- list()
long_genus <- list()
long_class <- list()
fig_upset_list <- list()
for (one_sample_type in sample_type) {
long_one <- long_species_sample[[one_sample_type]] %>% filter(date >= as.Date("2015-01-01")) %>% filter(!str_detect(species, "_X")) %>% filter(fraction_name_original !=
"> 20 um") %>% group_by(division, class, order, family, genus, species) %>% summarize(n_reads = sum(n_reads), n_samples = n()) %>% rename_at(vars(contains("n_")),
funs(str_c(., str_replace_all(one_sample_type, " ", "_"), sep = "_"))) %>% ungroup()
long_species[[one_sample_type]] <- long_one
long_one <- long_species_sample[[one_sample_type]] %>% filter(date >= as.Date("2015-01-01")) %>% filter(!str_detect(species, "_X")) %>% filter(fraction_name_original !=
"> 20 um") %>% group_by(division, class, order, family, genus) %>% summarize(n_reads = sum(n_reads), n_samples = n()) %>% rename_at(vars(contains("n_")),
funs(str_c(., str_replace_all(one_sample_type, " ", "_"), sep = "_"))) %>% ungroup()
long_genus[[one_sample_type]] <- long_one
long_one <- long_class_sample[[one_sample_type]] %>% filter(date >= as.Date("2015-01-01")) %>% filter(fraction_name_original != "> 20 um") %>%
group_by(division, class) %>% summarize(n_reads = sum(n_reads), n_samples = n()) %>% rename_at(vars(contains("n_")), funs(str_c(., str_replace_all(one_sample_type,
" ", "_"), sep = "_"))) %>% ungroup()
long_class[[one_sample_type]] <- long_one
}
long_class_comparison <- long_class %>% purrr::reduce(full_join)
long_genus_comparison <- long_genus %>% purrr::reduce(full_join)
long_species_comparison <- long_species %>% purrr::reduce(full_join)
# Class ----------
cat("Class not found in one type of sample\n")Class not found in one type of sample
18S filter
| division | class | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|
| Chlorophyta | Prasino-Clade-V | NA | NA | 0.1765574 | 27 | NA | NA |
18S sort
| division | class | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|
| Chlorophyta | Trebouxiophyceae | 0.0004002 | 3 | 0.0004331 | 3 | NA | NA |
| Rhodophyta | Florideophyceae | 0.0736053 | 27 | 0.0017249 | 9 | NA | NA |
| Chlorophyta | Prasino-Clade-V | NA | NA | 0.1765574 | 27 | NA | NA |
16S filter
| division | class | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|
| Chlorophyta | Ulvophyceae | 0.0197181 | 22 | NA | NA | 0.3029099 | 1 |
| Ochrophyta | MOCH-2 | 0.0314126 | 26 | NA | NA | 0.0383595 | 9 |
Genus found in the three types of samples
18S filter
kable(filter(long_genus_comparison, (!is.na(n_samples_18S_filter) & !is.na(n_samples_18S_sort) & !is.na(n_samples_16S_plastid))))| division | class | order | family | genus | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | 0.2047292 | 30 | 0.0011887 | 2 | 0.9280385 | 21 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | 0.0004832 | 1 | 0.0272823 | 22 | 0.0013399 | 1 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | 0.0280184 | 29 | 0.0181827 | 22 | 0.0015760 | 1 |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | 0.5899594 | 65 | 4.5264901 | 30 | 1.1062379 | 22 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | 8.3011827 | 33 | 0.0000594 | 1 | 3.3903198 | 24 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | 0.8712445 | 35 | 4.5158115 | 28 | 7.9617359 | 50 |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | 0.0138549 | 18 | 6.1388612 | 28 | 0.3357026 | 20 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | 0.4170779 | 55 | 0.1027584 | 24 | 3.7710088 | 35 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | 4.8424843 | 39 | 2.8469791 | 27 | 4.2101937 | 24 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | 2.5663612 | 34 | 1.0900795 | 24 | 0.0336542 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | 3.1823140 | 68 | 0.0862048 | 12 | 1.3921588 | 38 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | 4.1161364 | 53 | 1.0791966 | 28 | 3.8921612 | 41 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | 0.0681147 | 25 | 0.0481983 | 18 | 0.0353992 | 7 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | 0.1638104 | 34 | 0.1899858 | 32 | 0.4149332 | 22 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | 0.0524154 | 29 | 0.0016350 | 3 | 0.0103929 | 8 |
Genus only found in one type of sample
18S filter
| division | class | order | family | genus | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chaetopeltidales | Chaetopeltidaceae | Planophila | 0.0003221 | 1 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Haematococcus | 0.0001605 | 1 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Pleurastrum | 0.0009742 | 3 | NA | NA | NA | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Desmococcus | 0.0000585 | 1 | NA | NA | NA | NA |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | 0.0001530 | 1 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Chlorothrix | 0.0018758 | 2 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Monostroma | 0.0150017 | 17 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Dilabifilum | 0.0002731 | 1 | NA | NA | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Teleaulax | 0.0000661 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Licmophora | 0.0007432 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Pteroncola | 0.0007406 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassionema | 0.0011473 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Eucampia | 0.0005298 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Shionodiscus | 0.0173100 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | 0.0017113 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | 0.0000685 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Stellarima | 0.0001769 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Amphora | 0.0057413 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cylindrotheca | 0.0002630 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | 0.0041444 | 12 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Encyonema | 0.0016082 | 7 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Haslea | 0.0011843 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | 0.0008912 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | 0.0002409 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pauliella | 0.0002739 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pleurosigma | 0.0011816 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudogomphonema | 0.0059717 | 11 | NA | NA | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3A | 0.0097964 | 9 | NA | NA | NA | NA |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Spumella | 0.0144548 | 5 | NA | NA | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pseudopedinella | 0.0001042 | 1 | NA | NA | NA | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Pylaiella | 0.0005950 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Hemineura | 0.0000743 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Phycodrys | 0.0000850 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Hapalidiaceae | 0.0003964 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Mesophyllum | 0.0253548 | 23 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Synarthrophyton | 0.0007193 | 2 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Stenogramme | 0.0015735 | 2 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gracilariales | Gracilariales_X | Curdiea | 0.0011262 | 4 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Halymeniales | Halymeniales_X | Pachymenia | 0.0000992 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Plocamiales | Plocamiales_X | Trematocarpus | 0.0004336 | 2 | NA | NA | NA | NA |
18S sort
| division | class | order | family | genus | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Skeletonema | NA | NA | NA | NA | 0.0000463 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Bacillaria | NA | NA | NA | NA | 0.0002977 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Luka_AeN707 | NA | NA | NA | NA | 0.0011928 | 2 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonadaceae_clade_A | NA | NA | NA | NA | 0.0002917 | 1 |
16S filter
| division | class | order | family | genus | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Oophila | NA | NA | 0.0001469 | 2 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Chlorellales | Chlorellales_X | Chlorella | NA | NA | 0.0001729 | 1 | NA | NA |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Prymnesiaceae | Dicrateria | NA | NA | 0.0064689 | 17 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Conticribra | NA | NA | 0.0001386 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Lauderia | NA | NA | 0.0000594 | 1 | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Helicopedinella | NA | NA | 0.0073091 | 5 | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Mesopedinella | NA | NA | 0.0004326 | 3 | NA | NA |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Aureococcus | NA | NA | 0.4391393 | 28 | NA | NA |
| Rhodophyta | Florideophyceae | Ahnfeltiales | Ahnfeltiaceae | Ahnfeltia | NA | NA | 0.0001100 | 1 | NA | NA |
Species found in the three types of samples
18S filter
kable(filter(long_species_comparison, (!is.na(n_samples_18S_filter) & !is.na(n_samples_18S_sort) & !is.na(n_samples_16S_plastid))))| division | class | order | family | genus | species | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | Bathycoccus_prasinos | 0.2047292 | 30 | 0.0011887 | 2 | 0.9280385 | 21 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | Mantoniella_squamata | 0.0004832 | 1 | 0.0272823 | 22 | 0.0013399 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | Geminigera_cryophila | 8.3011827 | 33 | 0.0000594 | 1 | 3.3903198 | 24 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_sp. | 0.0004761 | 1 | 4.5158115 | 28 | 0.0948484 | 9 |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | Chrysochromulina_sp. | 0.0138549 | 18 | 6.1388612 | 28 | 0.3357026 | 20 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_sp. | 4.8105895 | 33 | 2.8469791 | 27 | 4.2101937 | 24 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_glacialis | 2.5659854 | 33 | 1.0900795 | 24 | 0.0336542 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_sp. | 1.3705387 | 32 | 0.0860340 | 11 | 0.7088026 | 12 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_cylindrus | 4.0610552 | 33 | 1.0791966 | 28 | 3.8587955 | 36 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | Florenciella_parvula | 0.0524154 | 29 | 0.0016350 | 3 | 0.0103929 | 8 |
long_genus_comparison_upset <- long_genus_comparison %>% select(genus, contains("samples")) %>% rename_at(vars(contains("n_")), funs(str_replace_all(.,
c(n_samples_ = "", `_` = " ", plastid = "filter"))))
fig_upset_list[["method genus"]] <- plot_upset_long(long_genus_comparison_upset, "../fig/upset_method_genus.png")Species only found in one type of sample
18S filter
| division | class | order | family | genus | species | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chaetopeltidales | Chaetopeltidaceae | Planophila | Planophila_sp. | 0.0003221 | 1 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_acidophila | 0.0001343 | 1 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_hedleyi | 0.0006203 | 2 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_kuwadae | 0.0013584 | 6 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Haematococcus | Haematococcus_zimbabwiensis | 0.0001605 | 1 | NA | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Pleurastrum | Pleurastrum_sp. | 0.0009742 | 3 | NA | NA | NA | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Desmococcus | Desmococcus_endolithicus | 0.0000585 | 1 | NA | NA | NA | NA |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | Chloroidium_ellipsoideum | 0.0001530 | 1 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Chlorothrix | Chlorothrix_sp. | 0.0018758 | 2 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Monostroma | Monostroma_grevillei | 0.0150017 | 17 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Dilabifilum | Dilabifilum_sp. | 0.0002731 | 1 | NA | NA | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_sp. | 0.0002160 | 2 | NA | NA | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_tepida | 0.0061607 | 7 | NA | NA | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Teleaulax | Teleaulax_sp. | 0.0000661 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Grammonema | Grammonema_striatula | 0.0003498 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Licmophora | Licmophora_grandis | 0.0007432 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Pteroncola | Pteroncola_inane | 0.0007406 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassionema | Thalassionema_frauenfeldii | 0.0011473 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_peruvianus | 0.0003611 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Eucampia | Eucampia_antarctica | 0.0005298 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_trioculatus | 0.0318947 | 6 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | Odontella_aurita | 0.0000751 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_pseudodelicatula | 0.0003758 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Shionodiscus | Shionodiscus_ritscheri | 0.0173100 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_antarctica | 0.0001088 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_oestrupii | 0.0001102 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_tumida | 0.0007959 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | Actinocyclus_actinochilus | 0.0017113 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Corethron | Corethron_inerme | 0.2140839 | 33 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | Rhizosolenia_fallax | 0.0000685 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Stellarima | Stellarima_microtrias | 0.0001769 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Amphora | Amphora_proteus | 0.0057413 | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cylindrotheca | Cylindrotheca_closterium | 0.0002630 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_gastroides | 0.0041444 | 12 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Encyonema | Encyonema_sp. | 0.0016082 | 7 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Haslea | Haslea_spicula | 0.0011843 | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_perminuta | 0.0000805 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_sp. | 0.0008106 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_dissipata | 0.0001239 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_sp. | 0.0001170 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pauliella | Pauliella_toeniata | 0.0002739 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pleurosigma | Pleurosigma_intermedium | 0.0011816 | 3 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_turgidula | 0.0001264 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudogomphonema | Pseudogomphonema_sp. | 0.0059717 | 11 | NA | NA | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3A | Parmales_env_3A_sp. | 0.0097964 | 9 | NA | NA | NA | NA |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Spumella | Spumella_elongata | 0.0144548 | 5 | NA | NA | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pseudopedinella | Pseudopedinella_sp. | 0.0001042 | 1 | NA | NA | NA | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Pylaiella | Pylaiella_littoralis | 0.0005950 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Hemineura | Hemineura_frondosa | 0.0000743 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Phycodrys | Phycodrys_rubens | 0.0000850 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Hapalidiaceae | Hapalidiaceae_sp. | 0.0003964 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Mesophyllum | Mesophyllum_sp. | 0.0253548 | 23 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Synarthrophyton | Synarthrophyton_patena | 0.0007193 | 2 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Chondrus | Chondrus_nipponicus | 0.0416973 | 22 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Stenogramme | Stenogramme_interrupta | 0.0015735 | 2 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gracilariales | Gracilariales_X | Curdiea | Curdiea_codiodes | 0.0011262 | 4 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Halymeniales | Halymeniales_X | Pachymenia | Pachymenia_orbicularis | 0.0000992 | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Plocamiales | Plocamiales_X | Trematocarpus | Trematocarpus_fragilis | 0.0004336 | 2 | NA | NA | NA | NA |
18S sort
kable(filter(long_species_comparison, (is.na(n_samples_18S_filter) & is.na(n_samples_16S_plastid))))| division | class | order | family | genus | species | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_daucoides | NA | NA | NA | NA | 0.0023399 | 3 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_sp. | NA | NA | NA | NA | 0.0001032 | 1 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_pouchetii | NA | NA | NA | NA | 0.0016326 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Skeletonema | Skeletonema_sp. | NA | NA | NA | NA | 0.0000463 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Bacillaria | Bacillaria_paxillifer | NA | NA | NA | NA | 0.0002977 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Luka_AeN707 | Luka_AeN707-96_sp. | NA | NA | NA | NA | 0.0011928 | 2 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_verruculosa | NA | NA | NA | NA | 0.0012825 | 1 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonadaceae_clade_A | Pelagomonadaceae_clade_A_sp. | NA | NA | NA | NA | 0.0002917 | 1 |
16S filter
| division | class | order | family | genus | species | n_reads_18S_filter | n_samples_18S_filter | n_reads_16S_plastid | n_samples_16S_plastid | n_reads_18S_sort | n_samples_18S_sort |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Oophila | Oophila_amblystomatis | NA | NA | 0.0001469 | 2 | NA | NA |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | Prasinoderma_coloniale | NA | NA | 0.0181827 | 22 | NA | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_disomata | NA | NA | 0.0001915 | 2 | NA | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_sp. | NA | NA | 4.5262986 | 28 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Chlorellales | Chlorellales_X | Chlorella | Chlorella_vulgaris | NA | NA | 0.0001729 | 1 | NA | NA |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Prymnesiaceae | Dicrateria | Dicrateria_sp. | NA | NA | 0.0064689 | 17 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Grammonema | Grammonema_striatulum | NA | NA | 0.0003316 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_sp. | NA | NA | 0.1027584 | 24 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Conticribra | Conticribra_weissflogii | NA | NA | 0.0001386 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Lauderia | Lauderia_annulata | NA | NA | 0.0000594 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | Odontella_sinensis | NA | NA | 0.1707281 | 25 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_nordenskioeldii | NA | NA | 0.0001708 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Corethron | Corethron_pennatum | NA | NA | 0.0263782 | 20 | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_pacifica | NA | NA | 0.0022029 | 4 | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Helicopedinella | Helicopedinella_sp. | NA | NA | 0.0073091 | 5 | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Mesopedinella | Mesopedinella_arctica | NA | NA | 0.0004326 | 3 | NA | NA |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Aureococcus | Aureococcus_anophagefferens | NA | NA | 0.4391393 | 28 | NA | NA |
| Rhodophyta | Florideophyceae | Ahnfeltiales | Ahnfeltiaceae | Ahnfeltia | Ahnfeltia_plicata | NA | NA | 0.0001100 | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Chondrus | Chondrus_crispus | NA | NA | 0.0011152 | 7 | NA | NA |
long_species_comparison_upset <- long_species_comparison %>% select(species, contains("samples")) %>% rename_at(vars(contains("n_")), funs(str_replace(.,
"n_samples_", "")))
fig_upset_list[["method species"]] <- plot_upset_long(long_species_comparison_upset, "../fig/upset_method_species.png")Write to Excel file
Comparison of species found in the different fractions for 18S filter and 18S sorted
Compute table of number of samples for each species (rows) vs the three fractions (columns)
Only keep
- 2015 samples because it is the only dataset for which we have the three types of samples
- Genera that do not contain _X
long_species_fraction <- list()
long_class_fraction <- list()
for (one_sample_type in sample_type[c(1, 3)]) {
long_one <- long_species_sample[[one_sample_type]] %>% filter(date >= as.Date("2015-01-01")) %>% filter(!str_detect(species, "_X")) %>% group_by(fraction_name_original,
division, class, order, family, genus, species) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>%
ungroup()
long_species_fraction[[one_sample_type]] <- long_one
long_one <- long_class_sample[[one_sample_type]] %>% filter(date >= as.Date("2015-01-01")) %>% group_by(fraction_name_original, division, class) %>%
summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>% ungroup()
long_class_fraction[[one_sample_type]] <- long_one
}
long_class_fraction_comparison <- long_class_fraction %>% purrr::reduce(full_join)
long_species_fraction_comparison <- long_species_fraction %>% purrr::reduce(full_join)
kable(long_class_fraction_comparison)| division | class | > 20 um | 0.2-3 um | 3-20 um | nano | pico |
|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | 7 | 5 | 5 | 1 | NA |
| Chlorophyta | Mamiellophyceae | 16 | 17 | 16 | 16 | 20 |
| Chlorophyta | Palmophyllophyceae | 4 | 14 | 15 | 1 | NA |
| Chlorophyta | Pyramimonadophyceae | 17 | 17 | 16 | 17 | NA |
| Chlorophyta | Trebouxiophyceae | 4 | NA | 3 | NA | NA |
| Chlorophyta | Ulvophyceae | 13 | 10 | 12 | NA | 1 |
| Cryptophyta | Cryptophyceae | 18 | 17 | 16 | 20 | 5 |
| Haptophyta | Prymnesiophyceae | 18 | 17 | 16 | 20 | 20 |
| Ochrophyta | Bacillariophyta | 18 | 17 | 16 | 20 | 20 |
| Ochrophyta | Bolidophyceae | 18 | 17 | 16 | 19 | 18 |
| Ochrophyta | Chrysophyceae | 12 | 16 | 16 | 1 | NA |
| Ochrophyta | Dictyochophyceae | 10 | 17 | 16 | 13 | NA |
| Ochrophyta | MOCH-2 | 10 | 12 | 14 | 9 | NA |
| Ochrophyta | Pelagophyceae | 18 | 17 | 16 | 20 | 20 |
| Ochrophyta | Phaeophyceae | 18 | 11 | 16 | 9 | NA |
| Rhodophyta | Florideophyceae | 17 | 12 | 15 | NA | NA |
| division | class | order | family | genus | species | > 20 um | 0.2-3 um | 3-20 um | nano | pico |
|---|---|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_kuwadae | 5 | 3 | 3 | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_raudensis | 1 | NA | 1 | 1 | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Pleurastrum | Pleurastrum_sp. | 1 | 1 | 2 | NA | NA |
| Chlorophyta | Chlorophyceae | Sphaeropleales | Sphaeropleales_X | Radiococcus | Radiococcus_polycoccus | 1 | NA | NA | NA | NA |
| Chlorophyta | Mamiellophyceae | Dolichomastigales | Dolichomastigaceae | Dolichomastigaceae-B | Dolichomastigaceae-B_sp. | 11 | 17 | 16 | NA | 2 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | Bathycoccus_prasinos | 4 | 16 | 14 | 1 | 20 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_polaris | 16 | 16 | 16 | 15 | 20 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | Prasinoderma_sp. | 4 | 14 | 15 | 1 | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_australis | 12 | 16 | 16 | 5 | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_gelidicola | 17 | 17 | 16 | 17 | NA |
| Chlorophyta | Trebouxiophyceae | Chlorellales | Chlorellales_X | Chlorella | Chlorella_sorokiniana | 1 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Chlorothrix | Chlorothrix_sp. | 3 | NA | 2 | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Monostroma | Monostroma_grevillei | 9 | 8 | 9 | NA | NA |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Ulothrix | Ulothrix_zonata | 2 | NA | NA | NA | NA |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Acrochaete | Acrochaete_leptochaete | 2 | 3 | 6 | NA | 1 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Dilabifilum | Dilabifilum_sp. | 1 | 1 | NA | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | Geminigera_cryophila | 18 | 17 | 16 | 20 | 4 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_tepida | 2 | 4 | 3 | NA | NA |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_antarctica | 18 | 17 | 16 | 20 | 18 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_sp. | 1 | NA | 1 | 9 | NA |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | Chrysochromulina_sp. | 3 | 9 | 9 | 20 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Asteroplanus | Asteroplanus_karianus | 18 | 17 | 16 | 18 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Grammonema | Grammonema_striatula | 1 | NA | 3 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Licmophora | Licmophora_grandis | 7 | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Pteroncola | Pteroncola_inane | 7 | 1 | 3 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedra | Synedra_hyperborea | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedropsis | Synedropsis_recta | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Tabularia | Tabularia_tabulata | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassiothrix | Thalassiothrix_longissima | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_debilis_2 | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_neogracilis | 18 | 17 | 16 | 13 | 17 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_peruvianus | 1 | 2 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_rostratus | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_socialis | 17 | 13 | 6 | 3 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Eucampia | Eucampia_antarctica | 2 | 2 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_sp. | 18 | 17 | 16 | 20 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | Odontella_aurita | 2 | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_glacialis | 18 | 17 | 16 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_pseudodelicatula | 3 | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_pseudodenticulata | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Shionodiscus | Shionodiscus_ritscheri | 11 | 2 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_antarctica | 1 | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_minima | 18 | 17 | 16 | 19 | 7 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_oceanica | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_sp. | 18 | 16 | 16 | 11 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_tumida | 1 | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | Actinocyclus_actinochilus | 10 | 2 | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Corethron | Corethron_inerme | 18 | 17 | 16 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Proboscia | Proboscia_alata | 6 | 5 | 7 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Proboscia | Proboscia_inermis | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | Rhizosolenia_imbricata_var_shrubsolei | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Stellarima | Stellarima_microtrias | 3 | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Achnanthes | Achnanthes_bongranii | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Amphora | Amphora_proteus | 12 | 2 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cocconeis | Cocconeis_stauroneiformis | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_gastroides | 6 | 3 | 9 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_laevis | 2 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_salina | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Dickieia | Dickieia_ulvacea | 4 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Encyonema | Encyonema_sp. | 6 | 1 | 6 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_cylindrus | 18 | 17 | 16 | 20 | 16 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_sublineata | 10 | 4 | 16 | 5 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Gyrosigma | Gyrosigma_limosum | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Haslea | Haslea_spicula | 3 | 2 | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_phyllepta | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_sp. | 4 | 2 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Naviculales | Naviculales_sp. | 4 | 7 | 11 | 3 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pinnularia | Pinnularia_microstauron | 1 | NA | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pleurosigma | Pleurosigma_intermedium | 3 | 1 | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_seriata | 14 | 9 | 15 | 4 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudogomphonema | Pseudogomphonema_sp. | 10 | 5 | 6 | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3A | Parmales_env_3A_sp. | 2 | 9 | NA | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3B | Parmales_env_3B_sp. | 16 | 17 | 16 | 19 | 11 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_laevis_clade | 18 | 17 | 16 | 8 | 14 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Dictyochales | Dictyocha | Dictyocha_speculum | 1 | NA | NA | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | Florenciella_parvula | 7 | 15 | 14 | 8 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_farcimen | 6 | 12 | 15 | 7 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_sp. | 1 | 1 | 5 | 2 | NA |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonas | Pelagomonas_calceolata | 2 | 11 | 4 | 1 | 14 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_menziesii | 13 | 4 | 10 | 1 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_sp. | 13 | 4 | 9 | 2 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Ectocarpus | Ectocarpus_siliculosus | 4 | NA | 1 | NA | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Phaeurus | Phaeurus_antarcticus | 15 | 8 | 14 | 6 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Pylaiella | Pylaiella_littoralis | 1 | NA | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Callithamniaceae | Diapse | Diapse_ptilota | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Phycodrys | Phycodrys_rubens | 4 | NA | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Colaconematales | Colaconematales_X | Palmaria | Palmaria_palmata | 1 | 2 | 3 | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Hapalidiaceae | Hapalidiaceae_sp. | 6 | 1 | NA | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Mesophyllum | Mesophyllum_sp. | 16 | 10 | 13 | NA | NA |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Synarthrophyton | Synarthrophyton_patena | 8 | 1 | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Chondrus | Chondrus_nipponicus | 17 | 7 | 15 | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Schottera | Schottera_nicaeensis | 1 | NA | NA | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Stenogramme | Stenogramme_interrupta | 3 | NA | 2 | NA | NA |
| Rhodophyta | Florideophyceae | Gracilariales | Gracilariales_X | Curdiea | Curdiea_codiodes | 7 | 1 | 3 | NA | NA |
| Rhodophyta | Florideophyceae | Plocamiales | Plocamiales_X | Trematocarpus | Trematocarpus_fragilis | 7 | 1 | 1 | NA | NA |
| Chlorophyta | Chlorophyceae | Chaetopeltidales | Chaetopeltidaceae | Planophila | Planophila_sp. | NA | 1 | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_acidophila | NA | 1 | NA | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_hedleyi | NA | 1 | 1 | NA | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Haematococcus | Haematococcus_zimbabwiensis | NA | 1 | NA | NA | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | Mantoniella_squamata | NA | 1 | NA | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_clade_B3 | NA | 7 | NA | NA | 18 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Teleaulax | Teleaulax_sp. | NA | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassionema | Thalassionema_frauenfeldii | NA | 1 | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_trioculatus | NA | 2 | 4 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | Rhizosolenia_fallax | NA | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_dissipata | NA | 1 | NA | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pauliella | Pauliella_toeniata | NA | 1 | NA | NA | NA |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Spumella | Spumella_elongata | NA | 5 | NA | NA | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pseudopedinella | Pseudopedinella_sp. | NA | 1 | NA | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Hemineura | Hemineura_frondosa | NA | 1 | NA | NA | NA |
| Rhodophyta | Florideophyceae | Halymeniales | Halymeniales_X | Pachymenia | Pachymenia_orbicularis | NA | 1 | NA | NA | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Desmococcus | Desmococcus_endolithicus | NA | NA | 1 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | Chloroidium_ellipsoideum | NA | NA | 1 | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_sp. | NA | NA | 2 | NA | NA |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_rex | NA | NA | 1 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_oestrupii | NA | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cylindrotheca | Cylindrotheca_closterium | NA | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_perminuta | NA | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_sp. | NA | NA | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_turgidula | NA | NA | 1 | NA | NA |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_laevis_f._inornata | NA | NA | 1 | NA | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Saccharina | Saccharina_japonica | NA | NA | 1 | NA | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_daucoides | NA | NA | NA | 2 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_sp. | NA | NA | NA | 1 | NA |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_pouchetii | NA | NA | NA | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Bacillaria | Bacillaria_paxillifer | NA | NA | NA | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Luka_AeN707 | Luka_AeN707-96_sp. | NA | NA | NA | 2 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_sp. | NA | NA | NA | 2 | 1 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_verruculosa | NA | NA | NA | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Skeletonema | Skeletonema_sp. | NA | NA | NA | NA | 1 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonadaceae_clade_A | Pelagomonadaceae_clade_A_sp. | NA | NA | NA | NA | 1 |
fig_upset_list[["filter_sort species"]] <- plot_upset_long(long_species_fraction_comparison, "../fig/upset_filter_sort.png")Comparison of species found in the different fractions for 18S filter
Compute table of number of samples for each species (rows) vs the three fractions (columns)
Only keep
- Genera that do not contain _X
We consider now ALL samples (will need to remove samples for which the > 20 um is missing)
long_species_fraction <- list()
long_genus_fraction <- list()
long_class_fraction <- list()
for (one_sample_type in sample_type[c(1)]) {
long_one <- long_species_sample[[one_sample_type]] %>% filter(!str_detect(species, "_X")) %>% group_by(fraction_name_original, division, class,
order, family, genus, species) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>%
ungroup()
long_species_fraction[[one_sample_type]] <- long_one
long_one <- long_species_sample[[one_sample_type]] %>% filter(!str_detect(species, "_X")) %>% group_by(fraction_name_original, division, class,
order, family, genus) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>% ungroup()
long_genus_fraction[[one_sample_type]] <- long_one
long_one <- long_class_sample[[one_sample_type]] %>% group_by(fraction_name_original, division, class) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original,
values_from = n_samples) %>% ungroup()
long_class_fraction[[one_sample_type]] <- long_one
}
long_class_fraction_comparison <- long_class_fraction[[one_sample_type]]
long_genus_fraction_comparison <- long_genus_fraction[[one_sample_type]]
long_species_fraction_comparison <- long_species_fraction[[one_sample_type]]
kable(long_class_fraction_comparison)| division | class | > 20 um | 0.2-3 um | 3-20 um |
|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | 8 | 6 | 6 |
| Chlorophyta | Mamiellophyceae | 30 | 42 | 43 |
| Chlorophyta | Palmophyllophyceae | 5 | 25 | 24 |
| Chlorophyta | Pyramimonadophyceae | 28 | 38 | 43 |
| Chlorophyta | Trebouxiophyceae | 9 | 1 | 7 |
| Chlorophyta | Ulvophyceae | 28 | 26 | 28 |
| Cryptophyta | Cryptophyceae | 35 | 42 | 43 |
| Haptophyta | Prymnesiophyceae | 32 | 42 | 42 |
| Ochrophyta | Bacillariophyta | 35 | 42 | 43 |
| Ochrophyta | Bolidophyceae | 34 | 42 | 43 |
| Ochrophyta | Chrysophyceae | 25 | 40 | 40 |
| Ochrophyta | Dictyochophyceae | 27 | 42 | 43 |
| Ochrophyta | MOCH-1 | 1 | 3 | 4 |
| Ochrophyta | MOCH-2 | 15 | 23 | 35 |
| Ochrophyta | Pelagophyceae | 34 | 42 | 43 |
| Ochrophyta | Phaeophyceae | 33 | 33 | 42 |
| Ochrophyta | Xanthophyceae | 1 | NA | NA |
| Rhodophyta | Bangiophyceae | 2 | 1 | NA |
| Rhodophyta | Florideophyceae | 34 | 36 | 42 |
| division | class | order | family | genus | > 20 um | 0.2-3 um | 3-20 um |
|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | 7 | 5 | 6 |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Pleurastrum | 1 | 1 | 2 |
| Chlorophyta | Chlorophyceae | Sphaeropleales | Sphaeropleales_X | Radiococcus | 1 | NA | NA |
| Chlorophyta | Mamiellophyceae | Dolichomastigales | Dolichomastigaceae | Dolichomastigaceae-B | 14 | 25 | 26 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | 13 | 40 | 40 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | 27 | 60 | 44 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | 5 | 25 | 24 |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | 43 | 66 | 77 |
| Chlorophyta | Trebouxiophyceae | Chlorellales | Chlorellales_X | Chlorella | 1 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Koliella | 1 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | 2 | 1 | 2 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Chlorothrix | 15 | 5 | 8 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Monostroma | 11 | 10 | 13 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Ulothrix | 2 | 2 | 1 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Acrochaete | 5 | 8 | 13 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Dilabifilum | 3 | 5 | 5 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | 35 | 42 | 43 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | 2 | 7 | 7 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | 33 | 42 | 44 |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | 6 | 23 | 31 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Asteroplanus | 34 | 38 | 42 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Grammonema | 8 | 2 | 8 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Licmophora | 17 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Pteroncola | 8 | 1 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedra | 2 | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedropsis | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Tabularia | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassionema | 2 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassiothrix | 4 | 2 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | 87 | 80 | 78 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Ditylum | 2 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Eucampia | 14 | 14 | 11 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Hemiaulus | 3 | 3 | 5 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | 36 | 43 | 54 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | 5 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | 40 | 44 | 43 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Shionodiscus | 19 | 3 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | 81 | 78 | 85 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | 27 | 7 | 5 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Asteromphalus | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Corethron | 35 | 41 | 42 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Coscinodiscus | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Guinardia | 1 | 1 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Proboscia | 19 | 12 | 22 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | 2 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Stellarima | 10 | 4 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Achnanthes | 3 | NA | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Amphora | 18 | 3 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cocconeis | 1 | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | 13 | 7 | 21 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Dickieia | 4 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Encyonema | 12 | 4 | 8 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | 48 | 49 | 71 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Gyrosigma | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Haslea | 11 | 12 | 14 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | 12 | 7 | 10 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Naviculales | 4 | 10 | 15 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pinnularia | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pleurosigma | 3 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | 29 | 21 | 32 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudogomphonema | 12 | 6 | 7 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3A | 5 | 27 | 12 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3B | 28 | 41 | 41 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | 34 | 47 | 49 |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Pedospumella | 1 | 1 | NA |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Spumella | 2 | 13 | 7 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Dictyochales | Dictyocha | 2 | 5 | 4 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | 13 | 38 | 40 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | 13 | 41 | 55 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonas | 5 | 28 | 16 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | 42 | 26 | 39 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Ectocarpus | 8 | 2 | 3 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Phaeurus | 27 | 9 | 20 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Pylaiella | 4 | NA | 2 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Saccharina | 1 | 2 | 6 |
| Ochrophyta | Xanthophyceae | Xanthophyceae_X | Xanthophyceae_XX | Botrydiopsis | 1 | NA | NA |
| Rhodophyta | Bangiophyceae | Bangiales | Bangiaceae | Porphyra | 1 | NA | NA |
| Rhodophyta | Bangiophyceae | Bangiales | Bangiaceae | Pyropia | 1 | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Callithamniaceae | Diapse | 2 | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Phycodrys | 7 | 2 | 7 |
| Rhodophyta | Florideophyceae | Colaconematales | Colaconematales_X | Palmaria | 14 | 17 | 18 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Hapalidiaceae | 7 | 2 | 1 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Mesophyllum | 31 | 22 | 35 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Synarthrophyton | 11 | 2 | 1 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Chondrus | 33 | 22 | 40 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Schottera | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Stenogramme | 4 | NA | 2 |
| Rhodophyta | Florideophyceae | Gracilariales | Gracilariales_X | Curdiea | 14 | 4 | 9 |
| Rhodophyta | Florideophyceae | Plocamiales | Plocamiales_X | Trematocarpus | 10 | 1 | 1 |
| Chlorophyta | Chlorophyceae | Chaetopeltidales | Chaetopeltidaceae | Planophila | NA | 1 | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Haematococcus | NA | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | NA | 4 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Plagioselmis | NA | 1 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Teleaulax | NA | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | NA | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pauliella | NA | 1 | 1 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pseudopedinella | NA | 1 | 2 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pteridomonas | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Dasyaceae | Dasya | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Hemineura | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Rhodomelaceae | Rhodomela | NA | 1 | 1 |
| Rhodophyta | Florideophyceae | Ceramiales | Sarcomeniaceae | Platysiphonia | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Kallymenia | NA | 1 | 2 |
| Rhodophyta | Florideophyceae | Halymeniales | Halymeniales_X | Pachymenia | NA | 1 | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Desmococcus | NA | NA | 1 |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Prasiola | NA | NA | 3 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | NA | NA | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cylindrotheca | NA | NA | 1 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Delisea | NA | NA | 1 |
| division | class | order | family | genus | species | > 20 um | 0.2-3 um | 3-20 um |
|---|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_hedleyi | 1 | 1 | 1 |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_kuwadae | 5 | 3 | 4 |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_raudensis | 1 | NA | 1 |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Pleurastrum | Pleurastrum_sp. | 1 | 1 | 2 |
| Chlorophyta | Chlorophyceae | Sphaeropleales | Sphaeropleales_X | Radiococcus | Radiococcus_polycoccus | 1 | NA | NA |
| Chlorophyta | Mamiellophyceae | Dolichomastigales | Dolichomastigaceae | Dolichomastigaceae-B | Dolichomastigaceae-B_sp. | 14 | 25 | 26 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | Bathycoccus_prasinos | 13 | 40 | 40 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_clade_B3 | 2 | 19 | 4 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_polaris | 25 | 41 | 40 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | Prasinoderma_sp. | 5 | 25 | 24 |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_australis | 16 | 28 | 34 |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_gelidicola | 27 | 38 | 43 |
| Chlorophyta | Trebouxiophyceae | Chlorellales | Chlorellales_X | Chlorella | Chlorella_sorokiniana | 1 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Koliella | Koliella_sempervirens | 1 | NA | NA |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | Chloroidium_saccharophila | 2 | 1 | 1 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Chlorothrix | Chlorothrix_sp. | 15 | 5 | 8 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Monostroma | Monostroma_grevillei | 11 | 10 | 13 |
| Chlorophyta | Ulvophyceae | Ulotrichales | Ulotrichales_X | Ulothrix | Ulothrix_zonata | 2 | 2 | 1 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Acrochaete | Acrochaete_leptochaete | 5 | 8 | 13 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Dilabifilum | Dilabifilum_sp. | 3 | 5 | 5 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | Geminigera_cryophila | 35 | 42 | 43 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_tepida | 2 | 7 | 7 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_antarctica | 32 | 42 | 42 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_sp. | 1 | NA | 1 |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | Chrysochromulina_sp. | 6 | 23 | 31 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Asteroplanus | Asteroplanus_karianus | 34 | 38 | 42 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Grammonema | Grammonema_striatula | 8 | 2 | 8 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Licmophora | Licmophora_grandis | 17 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Pteroncola | Pteroncola_inane | 8 | 1 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedra | Synedra_hyperborea | 2 | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Synedropsis | Synedropsis_recta | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Tabularia | Tabularia_tabulata | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassionema | Thalassionema_frauenfeldii | 2 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Thalassiothrix | Thalassiothrix_longissima | 4 | 2 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_danicus | 4 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_debilis_2 | 12 | 9 | 9 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_dichaeta | 3 | 3 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_neogracilis | 32 | 37 | 42 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_peruvianus | 2 | 3 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_rostratus | 10 | 3 | 7 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_socialis | 24 | 21 | 13 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Ditylum | Ditylum_sol | 2 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Eucampia | Eucampia_antarctica | 14 | 14 | 11 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Hemiaulus | Hemiaulus_sinensis | 3 | 3 | 5 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_sp. | 35 | 41 | 43 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_trioculatus | 1 | 2 | 11 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | Odontella_aurita | 2 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Odontella | Odontella_mobiliensis | 3 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_glacialis | 35 | 42 | 41 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_pseudodelicatula | 3 | 2 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_pseudodenticulata | 2 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Shionodiscus | Shionodiscus_ritscheri | 19 | 3 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_antarctica | 1 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_minima | 34 | 40 | 43 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_oceanica | 1 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_rotula | 1 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_sp. | 32 | 36 | 35 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_tumida | 12 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | Actinocyclus_actinochilus | 22 | 5 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Actinocyclus | Actinocyclus_curvatulus | 5 | 2 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Asteromphalus | Asteromphalus_sp. | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Corethron | Corethron_inerme | 35 | 41 | 42 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Coscinodiscus | Coscinodiscus_concinnus | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Coscinodiscus | Coscinodiscus_jonesianus | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Guinardia | Guinardia_solstherfothii | 1 | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Proboscia | Proboscia_alata | 18 | 12 | 22 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Proboscia | Proboscia_inermis | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | Rhizosolenia_imbricata_var_shrubsolei | 2 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Stellarima | Stellarima_microtrias | 10 | 4 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Achnanthes | Achnanthes_bongranii | 3 | NA | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Amphora | Amphora_proteus | 18 | 3 | 3 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cocconeis | Cocconeis_stauroneiformis | 1 | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_gastroides | 9 | 7 | 21 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_laevis | 3 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cymbella | Cymbella_salina | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Dickieia | Dickieia_ulvacea | 4 | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Encyonema | Encyonema_sp. | 12 | 4 | 8 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_cylindrus | 35 | 42 | 43 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_sublineata | 13 | 7 | 28 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Gyrosigma | Gyrosigma_limosum | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Haslea | Haslea_spicula | 11 | 12 | 14 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_lanceolata | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_phyllepta | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_sp. | 10 | 7 | 9 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Naviculales | Naviculales_sp. | 4 | 10 | 15 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pinnularia | Pinnularia_microstauron | 1 | NA | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pleurosigma | Pleurosigma_intermedium | 3 | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_seriata | 29 | 21 | 31 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudogomphonema | Pseudogomphonema_sp. | 12 | 6 | 7 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3A | Parmales_env_3A_sp. | 5 | 27 | 12 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3B | Parmales_env_3B_sp. | 28 | 41 | 41 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_laevis_clade | 34 | 41 | 43 |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Pedospumella | Pedospumella_encystans | 1 | 1 | NA |
| Ochrophyta | Chrysophyceae | Chrysophyceae_X | Chrysophyceae_Clade-C | Spumella | Spumella_elongata | 2 | 13 | 7 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Dictyochales | Dictyocha | Dictyocha_speculum | 2 | 5 | 4 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | Florenciella_parvula | 13 | 38 | 40 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_farcimen | 10 | 31 | 42 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_sp. | 3 | 10 | 13 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonas | Pelagomonas_calceolata | 5 | 28 | 16 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_menziesii | 22 | 9 | 16 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_sp. | 20 | 16 | 23 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Ectocarpus | Ectocarpus_siliculosus | 8 | 2 | 3 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Phaeurus | Phaeurus_antarcticus | 27 | 9 | 20 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Pylaiella | Pylaiella_littoralis | 4 | NA | 2 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Saccharina | Saccharina_japonica | 1 | 2 | 6 |
| Ochrophyta | Xanthophyceae | Xanthophyceae_X | Xanthophyceae_XX | Botrydiopsis | Botrydiopsis_callosa | 1 | NA | NA |
| Rhodophyta | Bangiophyceae | Bangiales | Bangiaceae | Porphyra | Porphyra_plocamiestris | 1 | NA | NA |
| Rhodophyta | Bangiophyceae | Bangiales | Bangiaceae | Pyropia | Pyropia_sp. | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Callithamniaceae | Diapse | Diapse_ptilota | 2 | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Phycodrys | Phycodrys_rubens | 7 | 2 | 7 |
| Rhodophyta | Florideophyceae | Colaconematales | Colaconematales_X | Palmaria | Palmaria_palmata | 14 | 17 | 18 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Hapalidiaceae | Hapalidiaceae_sp. | 7 | 2 | 1 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Mesophyllum | Mesophyllum_sp. | 31 | 22 | 35 |
| Rhodophyta | Florideophyceae | Corallinales | Corallinales_X | Synarthrophyton | Synarthrophyton_patena | 11 | 2 | 1 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Chondrus | Chondrus_nipponicus | 33 | 22 | 40 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Schottera | Schottera_nicaeensis | 1 | NA | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Stenogramme | Stenogramme_interrupta | 4 | NA | 2 |
| Rhodophyta | Florideophyceae | Gracilariales | Gracilariales_X | Curdiea | Curdiea_codiodes | 14 | 4 | 9 |
| Rhodophyta | Florideophyceae | Plocamiales | Plocamiales_X | Trematocarpus | Trematocarpus_fragilis | 10 | 1 | 1 |
| Chlorophyta | Chlorophyceae | Chaetopeltidales | Chaetopeltidaceae | Planophila | Planophila_sp. | NA | 1 | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_acidophila | NA | 1 | NA |
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Haematococcus | Haematococcus_zimbabwiensis | NA | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | Mantoniella_squamata | NA | 4 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Plagioselmis | Plagioselmis_nannoplanctica | NA | 1 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Teleaulax | Teleaulax_sp. | NA | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_gelidus | NA | 3 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Guinardia | Guinardia_delicatula | NA | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Radial-centric-basal-Coscinodiscophyceae | Rhizosolenia | Rhizosolenia_fallax | NA | 1 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_dissipata | NA | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pauliella | Pauliella_toeniata | NA | 1 | 1 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_sp. | NA | 6 | 5 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pseudopedinella | Pseudopedinella_sp. | NA | 1 | 2 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Pedinellales | Pteridomonas | Pteridomonas_danica | NA | 1 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_anceps | NA | 1 | NA |
| Rhodophyta | Bangiophyceae | Bangiales | Bangiaceae | Pyropia | Pyropia_dentata | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Dasyaceae | Dasya | Dasya_collabens | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Delesseriaceae | Hemineura | Hemineura_frondosa | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Ceramiales | Rhodomelaceae | Rhodomela | Rhodomela_confervoides | NA | 1 | 1 |
| Rhodophyta | Florideophyceae | Ceramiales | Sarcomeniaceae | Platysiphonia | Platysiphonia_victoriae | NA | 1 | NA |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Kallymenia | Kallymenia_tasmanica | NA | 1 | 2 |
| Rhodophyta | Florideophyceae | Halymeniales | Halymeniales_X | Pachymenia | Pachymenia_orbicularis | NA | 1 | NA |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Desmococcus | Desmococcus_endolithicus | NA | NA | 1 |
| Chlorophyta | Trebouxiophyceae | Prasiolales | Prasiolales_X | Prasiola | Prasiola_crispa | NA | NA | 3 |
| Chlorophyta | Trebouxiophyceae | Watanabea-Clade | Watanabea-Clade_X | Chloroidium | Chloroidium_ellipsoideum | NA | NA | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_sp. | NA | NA | 2 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_rex | NA | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_sp. | NA | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_oestrupii | NA | NA | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Cylindrotheca | Cylindrotheca_closterium | NA | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Navicula | Navicula_perminuta | NA | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Nitzschia | Nitzschia_sp. | NA | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_turgidula | NA | NA | 1 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_laevis_f._inornata | NA | NA | 1 |
| Rhodophyta | Florideophyceae | Gigartinales | Gigartinales_X | Delisea | Delisea_pulchra | NA | NA | 1 |
fig_upset_list[["filter genus"]] <- plot_upset_long(long_genus_fraction_comparison, "../fig/upset_filter_genus.png")fig_upset_list[["filter species"]] <- plot_upset_long(long_species_fraction_comparison, "../fig/upset_filter_species.png")Comparison of species found in the different fractions for 18S sort
Compute table of number of samples for each species (rows) vs the three fractions (columns)
Only keep
- Genera that do not contain _X
We consider now ALL samples (will need to remove samples for which the > 20 um is missing)
long_species_fraction <- list()
long_class_fraction <- list()
for (one_sample_type in sample_type[c(3)]) {
long_one <- long_species_sample[[one_sample_type]] %>% filter(!str_detect(species, "_X")) %>% group_by(fraction_name_original, division, class,
order, family, genus, species) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>%
ungroup()
long_species_fraction[[one_sample_type]] <- long_one
long_one <- long_species_sample[[one_sample_type]] %>% filter(!str_detect(species, "_X")) %>% group_by(fraction_name_original, division, class,
order, family, genus) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original, values_from = n_samples) %>% ungroup()
long_genus_fraction[[one_sample_type]] <- long_one
long_one <- long_class_sample[[one_sample_type]] %>% group_by(fraction_name_original, division, class) %>% summarize(n_samples = n()) %>% pivot_wider(names_from = fraction_name_original,
values_from = n_samples) %>% ungroup()
long_class_fraction[[one_sample_type]] <- long_one
}
long_class_fraction_comparison <- long_class_fraction[[one_sample_type]]
long_genus_fraction_comparison <- long_genus_fraction[[one_sample_type]]
long_species_fraction_comparison <- long_species_fraction[[one_sample_type]]
kable(long_class_fraction_comparison)| division | class | nano | pico |
|---|---|---|---|
| Chlorophyta | Chlorophyceae | 1 | NA |
| Chlorophyta | Mamiellophyceae | 16 | 20 |
| Chlorophyta | Palmophyllophyceae | 1 | NA |
| Chlorophyta | Pyramimonadophyceae | 17 | NA |
| Cryptophyta | Cryptophyceae | 20 | 5 |
| Haptophyta | Prymnesiophyceae | 20 | 20 |
| Ochrophyta | Bacillariophyta | 20 | 20 |
| Ochrophyta | Bolidophyceae | 19 | 18 |
| Ochrophyta | Chrysophyceae | 1 | NA |
| Ochrophyta | Dictyochophyceae | 13 | NA |
| Ochrophyta | MOCH-2 | 9 | NA |
| Ochrophyta | Pelagophyceae | 20 | 20 |
| Ochrophyta | Phaeophyceae | 9 | NA |
| Chlorophyta | Ulvophyceae | NA | 1 |
| division | class | order | family | genus | nano | pico |
|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | 1 | 20 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | 15 | 38 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | 1 | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | 22 | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | 2 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | 20 | 4 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | 1 | NA |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | 30 | 20 |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | 20 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Asteroplanus | 18 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | 16 | 19 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | 20 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | 30 | 8 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Bacillaria | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | 25 | 16 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Luka_AeN707 | 2 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Naviculales | 3 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | 6 | 1 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3B | 19 | 11 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | 8 | 14 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | 8 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | 10 | NA |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonas | 1 | 14 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | 3 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Phaeurus | 6 | NA |
| Chlorophyta | Mamiellophyceae | Dolichomastigales | Dolichomastigaceae | Dolichomastigaceae-B | NA | 2 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Acrochaete | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Skeletonema | NA | 1 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonadaceae_clade_A | NA | 1 |
| division | class | order | family | genus | species | nano | pico |
|---|---|---|---|---|---|---|---|
| Chlorophyta | Chlorophyceae | Chlamydomonadales | Chlamydomonadales_X | Chlamydomonas | Chlamydomonas_raudensis | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Bathycoccaceae | Bathycoccus | Bathycoccus_prasinos | 1 | 20 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Mantoniella | Mantoniella_squamata | 1 | NA |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_polaris | 15 | 20 |
| Chlorophyta | Palmophyllophyceae | Prasinococcales | Prasinococcales-Clade-B | Prasinoderma | Prasinoderma_sp. | 1 | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_australis | 5 | NA |
| Chlorophyta | Pyramimonadophyceae | Pyramimonadales | Pyramimonadaceae | Pyramimonas | Pyramimonas_gelidicola | 17 | NA |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Falcomonas | Falcomonas_daucoides | 2 | 1 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Geminigera | Geminigera_cryophila | 20 | 4 |
| Cryptophyta | Cryptophyceae | Cryptomonadales | Cryptomonadales_X | Hemiselmis | Hemiselmis_sp. | 1 | NA |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_antarctica | 20 | 18 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_pouchetii | 1 | 1 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_sp. | 9 | NA |
| Haptophyta | Prymnesiophyceae | Prymnesiales | Chrysochromulinaceae | Chrysochromulina | Chrysochromulina_sp. | 20 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Araphid-pennate | Asteroplanus | Asteroplanus_karianus | 18 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_neogracilis | 13 | 17 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Chaetoceros | Chaetoceros_socialis | 3 | 2 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Minidiscus | Minidiscus_sp. | 20 | 4 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Porosira | Porosira_glacialis | 1 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_minima | 19 | 7 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Thalassiosira | Thalassiosira_sp. | 11 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Bacillaria | Bacillaria_paxillifer | 1 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_cylindrus | 20 | 16 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Fragilariopsis | Fragilariopsis_sublineata | 5 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Luka_AeN707 | Luka_AeN707-96_sp. | 2 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Naviculales | Naviculales_sp. | 3 | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_seriata | 4 | NA |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Raphid-pennate | Pseudo-nitzschia | Pseudo-nitzschia_sp. | 2 | 1 |
| Ochrophyta | Bolidophyceae | Parmales | Parmales_env_3 | Parmales_env_3B | Parmales_env_3B_sp. | 19 | 11 |
| Ochrophyta | Bolidophyceae | Parmales | Triparmaceae | Triparma | Triparma_laevis_clade | 8 | 14 |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Florenciella | Florenciella_parvula | 8 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_farcimen | 7 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_sp. | 2 | NA |
| Ochrophyta | Dictyochophyceae | Dictyochophyceae_X | Florenciellales | Pseudochattonella | Pseudochattonella_verruculosa | 1 | NA |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonas | Pelagomonas_calceolata | 1 | 14 |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_menziesii | 1 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Desmarestia | Desmarestia_sp. | 2 | NA |
| Ochrophyta | Phaeophyceae | Phaeophyceae_X | Phaeophyceae_XX | Phaeurus | Phaeurus_antarcticus | 6 | NA |
| Chlorophyta | Mamiellophyceae | Dolichomastigales | Dolichomastigaceae | Dolichomastigaceae-B | Dolichomastigaceae-B_sp. | NA | 2 |
| Chlorophyta | Mamiellophyceae | Mamiellales | Mamiellaceae | Micromonas | Micromonas_clade_B3 | NA | 18 |
| Chlorophyta | Ulvophyceae | Ulvales-relatives | Ulvales-relatives_X | Acrochaete | Acrochaete_leptochaete | NA | 1 |
| Haptophyta | Prymnesiophyceae | Phaeocystales | Phaeocystaceae | Phaeocystis | Phaeocystis_rex | NA | 1 |
| Ochrophyta | Bacillariophyta | Bacillariophyta_X | Polar-centric-Mediophyceae | Skeletonema | Skeletonema_sp. | NA | 1 |
| Ochrophyta | Pelagophyceae | Pelagomonadales | Pelagomonadaceae | Pelagomonadaceae_clade_A | Pelagomonadaceae_clade_A_sp. | NA | 1 |
fig_upset_list[["sort genus"]] <- plot_upset_long(long_genus_fraction_comparison, "../fig/upset_sort_genus.png")fig_upset_list[["sort species"]] <- plot_upset_long(long_species_fraction_comparison, "../fig/upset_sort_species.png")Figures
Class legend
dummy <- long[["18S filter surface"]] %>%
count(class, wt= n_reads)
legend_class <- ggplot(dummy, aes (x = class, y = n, fill = class)) +
geom_col() +
scale_fill_manual(values = class_colors, drop = FALSE) +
guides(fill = guide_legend(title.position="top",
ncol = 6, byrow = TRUE))
legend_class legend_class <- ggpubr::get_legend(legend_class +
# create some space to the left of the legend
theme(legend.box.margin = margin(t = 0, r = 0, b = 0, l = 0))
)
ggpubr::as_ggplot(legend_class)List of genera
Figure 2 - Treemap
Cowplot - DO NOT USE
treemap_18S_filt <- cowplot::plot_grid(treemap_class[["18S filter 0.2 um surface"]]$gg + ggtitle("0.2 µm"), treemap_class[["18S filter 3 um surface"]]$gg +
ggtitle("3 µm"), treemap_class[["18S filter 20 um surface"]]$gg + ggtitle("20 µm"), ncol = 1)
treemap_18S_sort <- cowplot::plot_grid(treemap_class[["18S sort pico surface"]]$gg, treemap_class[["18S sort nano surface"]]$gg, treemap_class[["fill in"]]$gg,
ncol = 1)
treemap_16S_filt <- cowplot::plot_grid(treemap_class[["16S plastid 0.2 um surface"]]$gg, treemap_class[["16S plastid 3 um surface"]]$gg, treemap_class[["16S plastid 20 um surface"]]$gg,
ncol = 1)
fig_2 <- cowplot::plot_grid(legend_class, NULL, bargraph_species[["18S filter surface"]]$gg + theme(legend.position = "none"), treemap_18S_filt,
bargraph_species[["18S sort surface"]]$gg + theme(legend.position = "none"), treemap_18S_sort, bargraph_species[["16S plastid surface"]]$gg +
theme(legend.position = "none"), treemap_16S_filt, ncol = 2, rel_widths = c(3, 1), rel_heights = c(1, 3, 3, 3), align = "v")
fig_2Patchwork
treemap_18S_filt <- (treemap_class[["18S filter 0.2 um surface"]]$gg + ggtitle("0.2 µm"))/(treemap_class[["18S filter 3 um surface"]]$gg + ggtitle("3 µm"))/(treemap_class[["18S filter 20 um surface"]]$gg +
ggtitle("20 µm"))
treemap_18S_sort <- (treemap_class[["18S sort pico surface"]]$gg + ggtitle("0.2 µm"))/(treemap_class[["18S sort nano surface"]]$gg + ggtitle("3 µm"))/plot_spacer()
treemap_16S_filt <- (treemap_class[["16S plastid 0.2 um surface"]]$gg + ggtitle("0.2 µm"))/(treemap_class[["16S plastid 3 um surface"]]$gg + ggtitle("3 µm"))/(treemap_class[["16S plastid 20 um surface"]]$gg +
ggtitle("20 µm"))
fig_2 <- ggpubr::as_ggplot(legend_class)/
(bargraph_species[["18S filter surface"]]$gg + theme(legend.position = "none") + treemap_18S_filt + plot_layout(widths = c(3, 1)))/(bargraph_species[["18S sort surface"]]$gg +
theme(legend.position = "none") + treemap_18S_sort + plot_layout(widths = c(3, 1)))/(bargraph_species[["16S plastid surface"]]$gg + theme(legend.position = "none") +
ggtitle("16S filter surface") + treemap_16S_filt + plot_layout(widths = c(3, 1))) + plot_layout(heights = c(1, 3, 3, 3))
fig_2Figure Supp - Treemap at genus level
treemap_18S_filt <- cowplot::plot_grid(treemap_genus[["18S filter 0.2 um surface"]]$gg + labs(title = "18S filter", subtitle = "0.2 µm"),
treemap_genus[["18S filter 3 um surface"]]$gg + labs(title = "", subtitle = "3 µm") +
theme(plot.title=element_blank()),
treemap_genus[["18S filter 20 um surface"]]$gg + labs(title = "", subtitle = "20 µm")+
theme(plot.title=element_blank()),
ncol=1)
treemap_18S_sort <- cowplot::plot_grid(treemap_genus[["18S sort pico surface"]]$gg + labs(title = "18S sort", subtitle = "pico"),
treemap_genus[["18S sort nano surface"]]$gg + labs(title = "", subtitle = "nano")+
theme(plot.title=element_blank()),
treemap_genus[["fill in"]]$gg,
ncol=1)
treemap_16S_filt <- cowplot::plot_grid(treemap_genus[["16S plastid 0.2 um surface"]]$gg + labs(title = "16S filter", subtitle = "0.2 µm"),
treemap_genus[["16S plastid 3 um surface"]]$gg + labs(title = "", subtitle = "3 µm")+
theme(plot.title=element_blank()),
treemap_genus[["16S plastid 20 um surface"]]$gg + labs(title = "", subtitle = "20 µm")+
theme(plot.title=element_blank()),
ncol=1)
fig_supp_treemap <- cowplot::plot_grid(treemap_18S_filt,
treemap_18S_sort,
treemap_16S_filt,
# labels = c("A" ,"B", "C"), label_x = 0.9,
ncol=3)
fig_supp_treemapFigure 3 - NMDS 18S filter
Cowplot - DO NOT USE
Figure sup - NMDS 16S plastid
Cowplot - DO NOT USE
Figure 4 - Heatmap 18S filter
Cowplot
fig_4 <- cowplot::plot_grid(heatmap_class_selected[["18S filter 0.2 um surface"]], heatmap_class_selected[["18S filter 3 um surface"]], heatmap_class_selected[["18S filter 20 um surface"]],
heatmap_species_selected[["18S filter 0.2 um surface"]], heatmap_species_selected[["18S filter 3 um surface"]], heatmap_species_selected[["18S filter 20 um surface"]],
labels = c("A", "B", "C", "D", "E", "F"), label_x = 0.9, nrow = 2, ncol = 3)
fig_4Patchwork
fig_4 <- heatmap_class_selected[["18S filter 0.2 um surface"]] + labs(title = "0.2 µm") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
heatmap_class_selected[["18S filter 3 um surface"]] + labs(title = "3 µm") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(),
axis.text.y = element_blank()) +
heatmap_class_selected[["18S filter 20 um surface"]] + labs(title = "20 µm") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(),
axis.text.y = element_blank()) +
heatmap_species_selected[["18S filter 0.2 um surface"]] + labs(title = "") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
heatmap_species_selected[["18S filter 3 um surface"]] + labs(title = "") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(),
axis.text.y = element_blank()) +
heatmap_species_selected[["18S filter 20 um surface"]] + labs(title = "") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(),
axis.text.y = element_blank()) +
plot_layout(nrow = 2, byrow = TRUE, guides = "collect")
fig_4Figure sup - Heatmap 18S sort
Cowplot - DO NOT USE
fig_heatmap_sort <- cowplot::plot_grid(heatmap_class_selected[["18S sort pico surface"]], heatmap_class_selected[["18S sort nano surface"]], heatmap_species_selected[["18S sort pico surface"]],
heatmap_species_selected[["18S sort nano surface"]], labels = c("A", "B", "C", "D"), label_x = 0.9, nrow = 2, ncol = 2)
fig_heatmap_sortPatchwork
fig_heatmap_sort <- heatmap_class_selected[["18S sort pico surface"]] + labs(title = "pico") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
heatmap_class_selected[["18S sort nano surface"]] + labs(title = "nano") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(),
axis.text.y = element_blank()) +
heatmap_species_selected[["18S sort pico surface"]] + labs(title = "") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +
heatmap_species_selected[["18S sort nano surface"]] + labs(title = "") + theme(axis.title.x = element_blank(), axis.title.y = element_blank(), axis.text.y = element_blank()) +
plot_layout(nrow = 2, byrow = TRUE, guides = "collect")
fig_heatmap_sortFigure 6 - Vertical Profile
Cowplot - DO NOT USE
legend <- cowplot::get_legend( bargraph_sample[["18S filter 0.2 um profile"]] +
# create some space to the left of the legend
theme(legend.box.margin = margin(0, 0, 0, 20))
)
fig_6 <- cowplot::plot_grid(bargraph_sample[["18S filter 0.2 um profile"]]+ theme(legend.position="none"),legend,
bargraph_sample[["18S filter 3 um profile"]] + theme(legend.position="none"),NULL,
bargraph_sample[["18S filter 20 um profile"]]+ theme(legend.position="none"),NULL,
labels = c("" ,"A","", "B","", "C"), label_x = 0.9,
nrow=3, ncol=2, rel_widths = c(3, 1.7))
fig_6Patchwork
fig_6 <- ggpubr::as_ggplot(legend_class)/(bargraph_sample[["18S filter 0.2 um profile"]] + theme(legend.position = "none") + labs(title = "0.2 µm") +
bargraph_sample[["18S filter 3 um profile"]] + theme(legend.position = "none", axis.title.y = element_blank()) + labs(title = "3 µm") + bargraph_sample[["18S filter 20 um profile"]] +
theme(legend.position = "none", axis.title.y = element_blank()) + labs(title = "20 µm")) + plot_layout(heights = c(0.3, 1))
fig_6Figure X - Upset R
- Problem is that upset does not provide a ggplot object. So need to save as png
- Use ggplotify library : https://cran.r-project.org/web/packages/ggplotify/vignettes/ggplotify.html
- But it heats a bit the plots
p1 <- cowplot::ggdraw() + cowplot::draw_image("../fig/upset_method_genus.png")
p2 <- cowplot::ggdraw() + cowplot::draw_image("../fig/upset_filter_genus.png")
p3 <- cowplot::ggdraw() + cowplot::draw_image("../fig/upset_sort_genus.png")
fig_X_upset <- cowplot::plot_grid(p1, p2, p3, labels = c("A", "B", "C"), label_x = 0.9, nrow = 3, ncol = 1)
fig_X_upsetSave figures
fig_path <- function(file) str_c("C:/daniel.vaulot@gmail.com/Papers/2020 Trefault Antarctic/Antarctic_overleaf_version_3.0/fig/", file)
ggsave(plot = fig_2, filename = fig_path("Figure_treeplot.pdf"), width = 12, height = 25, scale = 2.5, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_3, filename = fig_path("Figure_NMDS.pdf"), width = 12, height = 18, scale = 1.75, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_4, filename = fig_path("Figure_heatmap.pdf"), width = 20, height = 10, scale = 2.2, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_6, filename = fig_path("Figure_vertical_profile.pdf"), width = 13, height = 8, scale = 2.2, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_X_upset, filename = fig_path("Figure_upset.pdf"), width = 8, height = 17, scale = 2.2, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_NMDS_plastid, filename = fig_path("Figure-sup_NMDS_16S_plastid.pdf"), width = 12, height = 18, scale = 1.75, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_heatmap_sort, filename = fig_path("Figure-sup_heatmap_18S_sort.pdf"), width = 12, height = 10, scale = 2, units = "cm", useDingbats = FALSE)
ggsave(plot = fig_supp_treemap, filename = fig_path("Figure-sup_treemap_genus.pdf"), width = 12, height = 12, scale = 2, units = "cm", useDingbats = FALSE)
Figure - sup_NMDS_16S_plastid.pdf
Figure - sup_treemap_genus.pdf
Figure_upset.pdf
Figure_vertical_profile.pdf
Figure_vertical_profile_side.pdf
Figure - sup_heatmap_18S_sort.pdfSaving Tables to Latex
Define function to format the tables
- Not used
- “X” = “\\cellcolor{gray}”
File path
Table - Data sets
one_sheet <- "Table data sets"
one_legend <- filter(legends, table == one_sheet)
one_caption <- one_legend$legend[1]
one_label <- one_legend$label[1]
one_file <- one_legend$file_name[1]
table <- readxl::read_excel(path = file_main, sheet = one_sheet, range = "A1:G4")
table <- xtable::xtable(table, label = one_label, caption = one_caption, align = c("l", "c", "c", "c", "c", "c", "c", "c"), digits = 0)
print(table, scalebox = 0.85, caption.placement = "top", include.rownames = FALSE, file = path_table(one_file), sanitize.text.function = sanitize.italics)Table - Samples
one_sheet <- "Table samples"
one_legend <- filter(legends, table == one_sheet)
one_caption <- one_legend$legend[1]
one_label <- one_legend$label[1]
one_file <- one_legend$file_name[1]
addtorow <- list()
addtorow$pos <- list(0, 0)
addtorow$command <- c("Date & Season & CTD & Chl & FCM & Nutrients & Profile & \\multicolumn{3}{c}{18S rRNA filter} & \\multicolumn{3}{c}{16S rRNA plastid filter} & \\multicolumn{2}{c}{18S rRNA sort} \\\\\n",
"& & & & & & & 0.2 $\\mu$m & 3 $\\mu$m & 20 $\\mu$m & 0.2 $\\mu$m & 3 $\\mu$m & 20 $\\mu$m & Pico & Nano \\\\\n")
table <- readxl::read_excel(path = file_main, sheet = one_sheet, range = "A3:O22", col_names = FALSE)
table <- xtable::xtable(table, label = one_label, caption = one_caption, align = c("l", "l", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c",
"c", "c", "c"), digits = 0)
print(table, scalebox = 0.75, caption.placement = "top", add.to.row = addtorow, include.colnames = FALSE, include.rownames = FALSE, file = path_table(one_file),
sanitize.text.function = sanitize.italics)Table - Vertical Profile
one_sheet <- "Table vertical profile"
one_legend <- filter(legends, table == one_sheet)
one_caption <- one_legend$legend[1]
one_label <- one_legend$label[1]
one_file <- one_legend$file_name[1]
table <- readxl::read_excel(path = file_main, sheet = one_sheet, range = "A1:K6")
table <- xtable::xtable(table, label = one_label, caption = one_caption, align = c("l", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c"),
digits = c(0, 0, 2, 1, 2, 1, 2, 2, 1, 0, 0, 0))
print(table, scalebox = 1, caption.placement = "top", include.rownames = FALSE, file = path_table(one_file), sanitize.text.function = sanitize.italics)